Literature DB >> 12587875

Variation in the effects of take-all disease on grain yield and quality of winter cereals in field experiments.

Richard J Gutteridge1, Geoffrey L Bateman, Alan D Todd.   

Abstract

Relationships between take-all intensity and grain yield and quality were determined in field experiments on cereal crops using regression analyses, usually based on single-point disease assessments made during anthesis or grain-filling. Different amounts of take-all were achieved by different methods of applying inoculum artificially (to wheat only) or by using different cropping sequences (in wheat, triticale or barley) or sowing dates (wheat only) in crops with natural inoculum. Regressions of yield or thousand-grain weight on take-all intensity during grain filling were similar to those on accumulated disease (area under the disease progress curve) when these were compared in one of the wheat experiments. Regressions of yield on take-all intensity were more often significant in wheat than in the less susceptible crops, triticale and barley, even when a wide range of disease intensities was present in the latter crops. The regressions usually had most significance when there were plots in the severe disease category. Thousand-grain weight and hectolitre weight usually responded similarly to total grain yield. Decreased yield was often accompanied by a significant increase in the percentage of small grains. When severe take-all was present in wheat, regressions showed that nitrogen uptake was usually impaired. This was sometimes accompanied, however, by increased percentage nitrogen in the grain as a consequence of smaller grain size with decreased endosperm. Significant effects of take-all, both positive and negative, on Hagberg falling number in wheat sometimes occurred. Significant regressions of yield on take-all assessed earlier than usual, ie during booting rather than grain-filling in wheat and triticale and during anthesis/grain-filling rather than ripening in barley, had steeper slopes. This is consistent with observations that severe disease that develops early can be particularly damaging, whilst the crops, especially barley, can later express tolerance by producing additional, healthy roots. The regression parameters, including maximum potential yield (y-axis intercept) and the extrapolated maximum yield loss, also varied according to the different growing conditions, including experimental treatments and other husbandry operations. These differences must be considered when assessing the economic potential of a control measure such as fungicidal seed treatment.

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Year:  2003        PMID: 12587875     DOI: 10.1002/ps.574

Source DB:  PubMed          Journal:  Pest Manag Sci        ISSN: 1526-498X            Impact factor:   4.845


  11 in total

1.  Comparison of barley succession and take-all disease as environmental factors shaping the rhizobacterial community during take-all decline.

Authors:  Karin Schreiner; Alexandra Hagn; Martina Kyselková; Yvan Moënne-Loccoz; Gerhard Welzl; Jean Charles Munch; Michael Schloter
Journal:  Appl Environ Microbiol       Date:  2010-06-04       Impact factor: 4.792

2.  Expression of a potato antimicrobial peptide SN1 increases resistance to take-all pathogen Gaeumannomyces graminis var. tritici in transgenic wheat.

Authors:  Wei Rong; Lin Qi; Jingfen Wang; Lipu Du; Huijun Xu; Aiyun Wang; Zengyan Zhang
Journal:  Funct Integr Genomics       Date:  2013-07-10       Impact factor: 3.410

3.  GmPGIP3 enhanced resistance to both take-all and common root rot diseases in transgenic wheat.

Authors:  Aiyun Wang; Xuening Wei; Wei Rong; Liang Dang; Li-Pu Du; Lin Qi; Hui-Jun Xu; Yanjun Shao; Zengyan Zhang
Journal:  Funct Integr Genomics       Date:  2014-12-07       Impact factor: 3.410

4.  Transgenic wheat expressing Thinopyrum intermedium MYB transcription factor TiMYB2R-1 shows enhanced resistance to the take-all disease.

Authors:  Xin Liu; Lihua Yang; Xianyao Zhou; Miaoping Zhou; Yan Lu; Lingjian Ma; Hongxiang Ma; Zengyan Zhang
Journal:  J Exp Bot       Date:  2013-04-01       Impact factor: 6.992

5.  Comparative transcriptome profiling of the early infection of wheat roots by Gaeumannomyces graminis var. tritici.

Authors:  Lirong Yang; Lihua Xie; Baoguo Xue; Paul H Goodwin; Xin Quan; Chuanlin Zheng; Taiguo Liu; Zhensheng Lei; Xiaojie Yang; Yueen Chao; Chao Wu
Journal:  PLoS One       Date:  2015-04-14       Impact factor: 3.240

6.  Genetic engineering of Pseudomonas chlororaphis GP72 for the enhanced production of 2-Hydroxyphenazine.

Authors:  Kaiquan Liu; Hongbo Hu; Wei Wang; Xuehong Zhang
Journal:  Microb Cell Fact       Date:  2016-07-28       Impact factor: 5.328

7.  Optimization of Production Conditions for Protoplasts and Polyethylene Glycol-Mediated Transformation of Gaeumannomyces tritici.

Authors:  Mei Wang; Jie Zhang; Lanying Wang; Lirong Han; Xing Zhang; Juntao Feng
Journal:  Molecules       Date:  2018-05-24       Impact factor: 4.411

8.  Activity of Fengycin and Iturin A Isolated From Bacillus subtilis Z-14 on Gaeumannomyces graminis Var. tritici and Soil Microbial Diversity.

Authors:  Jiawen Xiao; Xiaojun Guo; Xinlei Qiao; Xuechao Zhang; Xiaomeng Chen; Dongdong Zhang
Journal:  Front Microbiol       Date:  2021-06-18       Impact factor: 5.640

9.  Exploring the resilience of wheat crops grown in short rotations through minimising the build-up of an important soil-borne fungal pathogen.

Authors:  V E McMillan; G Canning; J Moughan; R P White; R J Gutteridge; K E Hammond-Kosack
Journal:  Sci Rep       Date:  2018-06-22       Impact factor: 4.379

10.  pH effect on strain-specific transcriptomes of the take-all fungus.

Authors:  Kévin Gazengel; Lionel Lebreton; Nicolas Lapalu; Joëlle Amselem; Anne-Yvonne Guillerm-Erckelboudt; Denis Tagu; Stéphanie Daval
Journal:  PLoS One       Date:  2020-07-30       Impact factor: 3.240

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